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Descriptive and Analytic Studies Descriptive and Analytic Studies Presenter’s Name Presenter’s Title Title of Event Date of Event Department of Health and Human Services Centers for Disease Control and Prevention Learning Objectives • Identify the following for an NCD problem: • Type of study to conduct • Sampling methods to use • Measure of association to calculate for a particular study • Interpret the results of descriptive and analytic studies. Descriptive and Analytic Studies 2 Lesson Overview • Reasons for conducting studies • Definition, characteristics, and analysis of: • Descriptive studies • Analytic studies • Methods of sampling Descriptive and Analytic Studies 3 Why Conduct Studies? To describe burden of disease or prevalence of risk factors, health behaviors, or other characteristics of a population that influences risk of disease • To determine causes or risk factors for illness • To determine relative effectiveness of interventions Descriptive and Analytic Studies 4 Taxonomy of Epidemiologic Studies: Figure 1 Descriptive and Analytic Studies 5 Descriptive or Analytic Studies? Descriptive studies • Generate hypotheses • Answer what, who, where, and when Analytic studies • Test hypotheses • Answer why and how Descriptive and Analytic Studies 6 DEFINITION AND CHARACTERISTICS OF DESCRIPTIVE STUDIES Descriptive and Analytic Studies 7 Descriptive Studies Characterize who, where, or when in relation to what (outcome) • Person: characteristics (age, sex, occupation) of the individuals affected by the outcome • Place: geography (residence, work, hospital) of the affected individuals • Time: when events (diagnosis, reporting; testing) occurred Descriptive and Analytic Studies 8 Types of Descriptive Studies Aggregate Individual Ecological Case Report Studies Case Series Cross- sectional Study Descriptive and Analytic Studies 9 Cross-Sectional Study as a Descriptive Study Purpose: To learn about the characteristics of a population at one point in time (like a photo “snap shot”) Design: No comparison group Population: All members of a small, defined group or a sample from a large group Results: Produces estimates of the prevalence of the population characteristic of interest Descriptive and Analytic Studies 10 When to Conduct a Cross- Sectional Study • To estimate prevalence of a health condition or prevalence of a behavior, risk factor, or potential for disease • To learn about characteristics such as knowledge, attitude and practices of individuals in a population • To monitor trends over time with serial cross- sectional studies Descriptive and Analytic Studies 11 Cross-Sectional Study Measures Prevalence of a condition: = number of existing cases / size of population (or population count) Descriptive and Analytic Studies 12 Example: Cross-Sectional Study Objective • To estimate the magnitude and patterns of violence against pregnant women Study • Population-based, household, cross-sectional study in Mbeya and Dar es Salaam, Tanzania, 2001-2002 Result • Violence experienced by 7% in Dar es Salaam and 12% in Mbeya Ref: Stöckl H, Watts C, Kilonzo Mbwambo JK. Physical violence by a partner during pregnancy in Tanzania: prevalence and risk factors. Reprod Health Matters. 2010 Nov;18(36):171-80. Descriptive and Analytic Studies 13 Studies to Track Trends in Newly Recognized Cases Incidence study • Newly reported or registered disease cases compared over time, place, or person • Population estimates or other population group totals used as denominators Ecological study • Rates are linked to the level of exposure to some agent for the group as a whole Descriptive and Analytic Studies 14 Example: Incidence Study Objective • To estimate the incidence and prevalence of diabetes in young persons in the United States Study • Annual diabetes death rates among youth aged <19 calculated from National Vital Statistics System data from 1968-2009 Result • Trends for diabetes death rates varied by age group Saydah, S, Imperatore, G., Geiss, L., & Gregg, E. (2012). Diabetes death rates among youths aged <19 years—United States, 1968-2009. MMWR, 61(43), 869-871 Descriptive and Analytic Studies 15 Example Incidence Study (continued) Saydah, S, Imperatore, G., Geiss, L., & Gregg, E. (2012). Diabetes death rates among youths aged <19 years—United States, 1968-2009. MMWR, 61(43), 869-871. Descriptive and Analytic Studies 16 Taxonomy of Epidemiologic Studies: Figure 2 Descriptive and Analytic Studies 17 Analytic Studies Definition Analytic studies test hypotheses about exposure- outcome relationships • Measure the association between exposure and outcome • Include a comparison group Descriptive and Analytic Studies 18 Developing Hypotheses • A hypothesis is an educated guess about an association that is testable in a scientific investigation. • Descriptive data (Who? What? Where? When?) provide information to develop hypotheses. • Hypotheses tend to be broad initially and are then refined to have a narrower focus. Descriptive and Analytic Studies 19 Developing Hypotheses Example Hypothesis: People who smoke shisha are more likely to get lung cancer than people who do not smoke shisha. • Exposure: smoking shisha • Outcome: lung cancer Hypothesis: ? • Exposure: ? • Outcome: ? Descriptive and Analytic Studies 20 Analytic Study Types Experimental Observational Studies Studies Randomized Cohort Control (Intervention) Trials Case-control Cross-sectional Descriptive and Analytic Studies 21 Cohort Studies What is a cohort? A well-defined group of individuals who share a common characteristic or experience • Example: Individuals born in the same year What are other examples of cohorts? Descriptive and Analytic Studies 22 Cohort Study (longitudinal study, follow-up study) • Participants classified according to exposure status and followed-up over time to ascertain outcome • Can be used to find multiple outcomes from a single exposure • Appropriate for rare exposures or defined cohorts • Ensures temporality (exposure occurs before observed outcome) Descriptive and Analytic Studies 23 Cohort Study Design Disease Exposed No Disease Study Exposure is Follow Population self-selected over time Disease Unexposed No Disease Descriptive and Analytic Studies 24 Types of Cohort Studies Prospective cohort studies • Group participants according to past or current exposure and follow-up into the future to determine if outcome occurs Retrospective cohort studies • At the time that the study is conducted, potential exposure and outcomes have already occurred in the past Descriptive and Analytic Studies 25 Prospective Cohort Studies Disease Exposed No Disease Study Population Disease Unexposed No Disease Start of study (Present) (Future) Descriptive and Analytic Studies 26 Retrospective Cohort Studies Disease Exposed No Disease Study Population Disease Unexposed No Disease Start of study (Past) (Present) Descriptive and Analytic Studies 27 When to Conduct a Cohort Study When the exposure is rare and the outcome is common • Agricultural pesticide use and cancer events To learn about multiple outcomes due to a single exposure • Health effects of a nuclear power plant accident Descriptive and Analytic Studies 28 Analysis of Cohort Studies Risk: Quantifies probability of experiencing the outcome of interest in a given population • Calculation: Number of new occurrences of outcome/population at risk Example: • 29 new cases of diabetes in a community • 100,000 people in the community at risk for diabetes • What is the risk of diabetes? 29/100,000 Descriptive and Analytic Studies 29 Analysis of Cohort Studies: Person-Time, Rate Quantifies occurrence of outcome in population by time Calculation: number of new cases during follow-up period Sum of time each study participant was followed and at risk of disease Example: 1,212 tunnel workers 160 deaths among tunnel workers 24,035 person-years at risk Mortality rate = 160 / 24,035 = 6.7 deaths per 1,000 workers per year Ref:. Stern et al. Heart Disease Mortality Among Bridge and Tunnel Officers Exposed to Carbon Monoxide. American Journal of Epidemiology.1988;128:1276-1288 Descriptive and Analytic Studies 30 Risk Ratio • Can also be called Relative Risk or RR • Quantifies a population’s risk of disease from a particular exposure • Calculation: Risk in the exposed group / Risk in the unexposed group Descriptive and Analytic Studies 31 Rate Ratio Compares the rates of disease in two groups that differ by demographic characteristics or exposure history Calculation: Rate for group of primary interest Rate for comparison group Descriptive and Analytic Studies 32 RR Strength Scales RR Strength RR 0.71 – 0.99 Weak 1.01 – 1.50 0.41 – 0.70 Moderate 1.51 – 3.00 0.00 – 0.40 Very strong >3.00 Oleckno WA. Essential epidemiology: principles and applications. Prospect Heights, IL 2002;108. Descriptive and Analytic Studies 33 Example: Risk Ratio Question: What is the relationship between being obese and getting type 2 diabetes? Risk in the exposed group (obese) = .00076 = 5.8 Risk in the unexposed group (non-obese) .00013 Risk Ratio = 5.8 Interpretation: The risk of diabetes among those who are obese is 5.8 times the risk among those who are not obese. Descriptive and Analytic Studies 34 Example: Person-Time Rate Ratio NHANES – Follow-up Study (male diabetics subset) • Original enrollment 1971- 1975 • Follow-up 1982 – 1984 • Complete follow-up on: Enrolled Died PY of F/U Diabetics 189 100 1414.7 Non-diabetics 3151 811 28,029.8 • Mortality Rate Ratio: • 100/1414.7 ÷ 811/28,029.8 = 70.7/1000 ÷ 28.9/1000= 2.5 Ref: Kleinman J, et al. Am J Epidemiol. 1988; 128:389-401. Descriptive
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